tammyreservoir Goto Github PK

2016-ml-contest

Machine learning contest - October 2016 TLE

3w

Promotes development of ML algorithms for early detection and classification of undesirable events in offshore oil wells.

3w_dataset

The first realistic and public dataset with rare undesirable real events in oil wells.

70-years-of-machine-learning-in-geoscience-in-review

Code to recreate the tutorial and figures in the book chapter.

anatomyofmatplotlib

Anatomy of Matplotlib -- tutorial developed for the SciPy conference

arcgis-python-api

Documentation and samples for ArcGIS API for Python

awesome-full-stack-machine-learning-courses

Curated list of publicly accessible machine learning engineering courses from CalTech, Columbia, Berkeley, MIT, and Stanford.

bhp_prediction_models

Injection data analysis for prediction of Bottom-hole pressure

bibmon

Python package that provides predictive models for fault detection, soft sensing, and process condition monitoring.

cfd_books_codes

CFD codes written based on examples in various books like Patnakar, Versteeg etc

cfd_fenics

This repository is a beginner-friendly introduction to Computational Fluid Dynamics (CFD) for those interested in developing their own CFD solver. It includes Jupyter notebooks with detailed instructions.

choke_size_prediction

A Gas flow rate via choke size prediction of bangladeshi oil-gas well using machine learning regressors.

computational-multiphase-flow

coms4995-s20

COMS W4995 Applied Machine Learning - Spring 20

coshnet

cursor

data-code-skin-xgboost

The Skin Factor of a wellbore in Volve Field was calculated as the prepared model was validated with the datasets of another wellbore. The data was cleaned and processed to import it into jupyter notebook. GridSearchCV was the hyperparameter tuning method and eXtreme Boosting was the model implemented.

dataviz

A book covering the fundamentals of data visualization

deep_ml_curriculum

Data and Machine Learning Curriculum for Oil, Gas, and Mining

deepfield

Machine learning framework for reservoir simulation

failure-classifier-to-maintenance

Building a machine learning model to classify failures

flood_mapping_feature_space_importance

ga-tcn-lstm

An Ensemble DL Model Tuned with Genetic Algorithm for Oil Production Forecasting.

gdg

Repository for Google Developer Group demos

geodatascience

Application of Machine Learning and Deep Neural Networks in Geology, Geophysics and Petroleum Engineers

geog-312

Introduction to GIS Programming

geoslicer

ignite

High-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently.

ipython-notebooks

Collection of ipython notebooks I have made over the years. Includes notebooks on geoscience, petroleum engineering, data science and more.

kaust-hackathon-in-geoscience

Multiphase flow in porous media governs the recovery of subsurface energy including hydrocarbon and geothermal, and their management usually requires intensive simulation runs to quantify subsurface uncertainties and optimize engineering operations, which are often expensive. In this project, we ask you to develop machine-learning-based surrogate m